code to reproduce the results of:

Marten, A., Garbaccio, R., and Wolverton, A. 2019 "Exploring the General
  Equilibrium Costs of Sector-Specific Environmental Regulations." Journal of
  the Association of Environmental and Resource Economists."

to reproduce the figures and tables in the paper use R to run the script
"examples/marten et al - 2019 - run experiments.R" from the top level directory

based on v1.0.7 of the SAGE CGE model documented in:

Marten, A., and Garbaccio, R. 2018. "An Applied General Equilibrium Model for
  the Analysis of Environmental Policy: SAGE v1.0 Technical Documentation."
  NCEE Working Paper 2018-05.
  https://www.epa.gov/environmental-economics/applied-general-equilibrium-model-analysis-environmental-policy-sage-v10

the SAM for the SAGE model relies on the proprietary state-level IMPLAN data set
available from http://www.implan.com. therefore, the benchmark data for the
model is not included in this repository. to build the model's dataset:

1.) using the implan software create an implan model for each state and the
    district of columbia from the implan software. the spreadsheet in
    build/data/implan/batch state models.xls will allow for the batch creation
    of the models to avoid creating them one by one

2.) from the implan software open up each state model and run "Social Accounts->
    IxC Social Accounting Matrix->Detail SAM->Export->Gams Single File" to
    export the data into a file readable by GAMS. the files should be named as
    XX.gms and placed in build/data/implan, where XX is the state abbreviation

3.) the model's dataset may then be created by running the R script
    build/build_default_datasets.R which will create the missing
    data/default_aggregation.gdx

4.) to create the alternative versions of the dataset without certain taxes used
    in the creation of figure 1 zero out the necessary taxes in line 281 of
    build/build_benchmark_file.gms and rerun build/build_default_datasets.R
    renaming the created dataset to match the names on line 813 in
    examples/marten et al - 2019 - run experiments.R
